AGENTIC

• Lead and execute SAP cloud projects, participating in the design, implementation, and deployment of SAP solutions on public cloud platforms. • Advise clients by providing technical and strategic expertise on SAP best practices and cloud optimization. • Monitor and optimize SAP system performance in the cloud to ensure scalability, efficiency, and cost optimization. • Diagnose and resolve SAP and cloud-related technical incidents. • Create and maintain detailed technical documentation for architectures, configurations, and implementations. • Collaborate with cross-functional internal teams (development, operations, etc.) to ensure successful delivery. • Stay current on the latest SAP and public cloud technologies, trends, and best practices.

• Conduct technical assessments and gap analyses across client environments (networks, identity, M365, Azure, AWS, endpoints, and security posture) • Design remediation plans and upgrade roadmaps based on risk prioritization and business impact • Lead end-to-end migration initiatives: discovery, architecture design, coordination, execution, and stabilization • Architect AWS and Azure environments, including multi-account strategies, networking, identity, and security baselines • Strengthen Active Directory environments (tiered administration models, privileged access management, GPO reviews, legacy protocol remediation, attack path reduction) • Enhance Microsoft 365 security (Entra ID Conditional Access, Identity Protection, Defender suite, Exchange Online security, Purview, Intune baselines) • Translate security and compliance frameworks (NIST CSF, NIST 800-53/171, CMMC, HIPAA, SOC 2, ISO 27001, PCI DSS, CIS Controls) into actionable technical implementations • Act as a senior escalation point for MSP, MSSP, and Incident Response teams • Support incident response engagements with deep expertise in identity, architecture, and forensic analysis • Apply an engineering mindset to improve efficiency through automation, scripting, and tooling where applicable

• Lead and mentor a team of AI engineers, driving technical excellence and delivery • Design and implement AI/ML solutions leveraging Azure platforms • Guide the adoption and effective use of tools like Copilot and AI Agents • Collaborate with cross-functional teams to translate business needs into AI-driven solutions • Ensure best practices in AI development, scalability, and performance

• Design, develop, and maintain data engineering pipelines using Azure Synapse Analytics and Databricks to support data warehousing and advanced analytics. • Develop interactive and informative dashboards and reports using Power BI for business decision-making. • Implement data integration, data modeling, and ETL/ELT processes, ensuring data quality and consistency across platforms. • Migrate and integrate data from SAP systems (SAP ECC, BPC, APO, SAP BI) to cloud-based environments and analytical tools. • Collaborate with cross-functional teams to understand data requirements and provide data-driven solutions for business needs. • Apply machine learning frameworks and tools for predictive analytics and data science projects. • Ensure data governance, security, and compliance best practices are followed throughout all data processes. • Manage and optimize data lake and data warehousing solutions to support efficient data processing and storage.

• Create detailed requirements and lead the execution of integration projects. • Document and manage business logic in automations using UiPath. • Administer workflows and intelligent data capture in GlobalCapture. • Ensure alignment between business stakeholders and the development team.

• Design and implement context pipelines for LLM-based systems. • Structure information to maximize model understanding and response quality. • Define strategies for prompt composition, context injection, and tool usage. • Build and optimize RAG pipelines using vector databases. • Implement document ingestion, chunking, embedding, and retrieval strategies. • Improve retrieval precision and reduce hallucinations in AI outputs. • Design and maintain prompt frameworks for AI agents and applications. • Optimize prompts through systematic testing and evaluation. • Integrate prompts with tool use, APIs, and agent workflows. • Structure knowledge bases for AI consumption. • Implement pipelines for data preprocessing, indexing, and embedding generation. • Manage semantic search and knowledge retrieval systems. • Analyze model performance and improve context efficiency. • Monitor latency, token usage, and system scalability. • Develop evaluation methods to measure prompt and context performance. • Work closely with AI Engineers, Data Engineers, and Product Teams. • Translate business requirements into AI-powered solutions. • Document context architectures and AI workflows.

• Support the end-to-end sales process, from opportunity creation to project notification. • Review contracts, Terms & Conditions, and sales documentation. • Execute quality reviews (Sales QA) to ensure accuracy and compliance. • Manage CRM queues and QA email inboxes. • Identify process gaps and propose operational improvements. • Collaborate effectively with cross-functional teams. • Maintain CRM data integrity and reporting accuracy.

• Develop and train ML/DL models using TensorFlow, PyTorch, or similar frameworks. • Process, explore, and validate large datasets. • Build, tune, and deploy machine learning pipelines. • Conduct statistical analysis, error analysis, and model optimization. • Document experiments, pipelines, and technical decisions. • Collaborate with product and engineering teams to align model design with business needs.

• Manage full lifecycle delivery for medium-to-large programs. • Lead planning, scheduling, risk management, communication, and governance. • Coordinate multi-disciplinary teams (engineering, QA, architecture, support). • Maintain budgets, forecasts, financial dashboards, and revenue tracking. • Present weekly status reports to internal and client stakeholders. • Oversee change management processes and escalation handling. • Drive resource allocation, timeline alignment, and milestone approvals. • Ensure customer satisfaction and strategic alignment.

• Architect end-to-end solutions on AWS, Azure, and Salesforce. • Lead client workshops, technical deep dives, demos, and POCs. • Respond to RFPs/RFIs and produce technical proposals. • Collaborate with Sales, Delivery, and Engineering to align architectural vision. • Ensure cloud solutions meet scalability, security, governance, and performance requirements. • Lead transition from pre-sales to delivery teams, ensuring alignment and clarity. • Provide technical leadership and mentorship to engineering teams.